A recurrent challenge in real‐world applications is autonomous management of the
executions at run‐time. In this vein, stream processing is a class of applications that compute …

70In the field of clean water treatment, the use of artificial intelligence is becoming
imperative to achieve two main objectives at present, the control of water quality and the …

Multi-core systems are any computing device nowadays and stream processing applications
are becoming recurrent workloads, demanding parallelism to achieve the desired quality of …

Stream processing is a parallel paradigm used in many application domains. With the
advance of graphics processing units (GPUs), their usage in stream processing applications …

O crescimento e disseminação das arquiteturas paralelas têm conduzido a busca por maior
poder computacional com hardware massivamente paralelo tais como as unidades de …

GPUs are massively parallel processors that allow solving problems that are not viable to
traditional processors like CPUs. However, implementing applications for GPUs is …

Latency or throughput is often critical performance metrics in stream processing.
Applications' performance can fluctuate depending on the input stream. This unpredictability …

Stream processing paradigm is present in several applications that apply computations over
continuous data flowing in the form of streams (eg, video feeds, image, and data analytics) …

Several real-world parallel applications are becoming more dynamic and long-running,
demanding online (at run-time) adaptations. Stream processing is a representative scenario …

Atualmente, uma parte significativa dos sistemas computacionais e aplicações do mundo
real demandam paralelismo para acelerar suas execuções. Embora a programação …